Analisis Konfigurasi Pohon Lanskap Dalam Mitigasi Urban Heat Island di Wilayah Kabupaten dan Kota: Studi Kasus Bogor dan Bekasi

Abstract

Urbanisasi dan alih fungsi lahan di kawasan metropolitan Jakarta meningkatkan luas permukaan terbangun, mengurangi vegetasi, serta memperkuat tekanan termal perkotaan. Bogor dan Bekasi berada dalam satu sistem metropolitan, tetapi memiliki tingkat urbanisasi, keterbangunan, penggunaan lahan, dan struktur vegetasi yang berbeda sehingga menyediakan gradasi kondisi yang relevan untuk mengkaji Urban Heat Island (UHI). Penelitian terdahulu di wilayah tersebut umumnya telah menjelaskan hubungan antara perubahan tutupan lahan, indeks vegetasi, dan suhu permukaan, tetapi belum banyak mengintegrasikan tutupan pohon, konfigurasi spasial vegetasi, kondisi termal, dan jasa lanskap dalam satu kerangka komparatif. Kesenjangan tersebut penting karena luas vegetasi yang tinggi belum tentu menghasilkan kapasitas mitigasi termal yang sama apabila vegetasi didominasi vegetasi rendah atau tersusun dalam petak-petak kecil dan terfragmentasi. Penelitian ini bertujuan: (1) mengidentifikasi pola spasial dan konfigurasi lanskap vegetasi pohon; (2) mengidentifikasi pola spasial Surface Urban Heat Island (SUHI); (3) menganalisis jasa lanskap RTH berbasis pohon serta keterkaitannya secara deskriptif dengan konfigurasi lanskap dan suhu permukaan; dan (4) menyusun arahan pengembangan dan penataan RTH untuk mitigasi UHI pada empat wilayah studi di Bogor dan Bekasi. Penelitian menggunakan citra Landsat 8 dan Landsat 9 tahun 2025 untuk menghasilkan klasifikasi tutupan lahan, Normalized Difference Vegetation Index (NDVI), dan Land Surface Temperature (LST). Tutupan lahan diklasifikasikan menggunakan Support Vector Machine (SVM), sedangkan konfigurasi vegetasi pohon dianalisis melalui percentage of landscape (PLAND), aggregation index (AI), largest patch index (LPI), patch density (PD), dan edge density (ED). Kondisi termal dievaluasi melalui LST dan Urban Thermal Field Variance Index (UTFVI) dengan suhu acuan gabungan 307,60 K. Keterkaitan konfigurasi vegetasi pohon dengan LST dianalisis menggunakan korelasi peringkat Spearman pada grid 1 km, sedangkan tutupan tajuk, penyimpanan karbon, penyerapan karbon, dan penghilangan polutan diestimasi menggunakan i-Tree Canopy secara komparatif antarwilayah. Zonasi prioritas RTH disusun melalui overlay tiga kriteria pada grid 1 km × 1 km. Kriteria termal ditetapkan pada LST >37,33 °C berdasarkan persentil ke-75 dari 4.565 sel dengan LST valid, kriteria vegetasi pada PLAND vegetasi pohon <5% sebagai ambang empiris kekurangan tutupan pohon, dan kriteria sosial pada kepadatan penduduk di atas median kecamatan masing-masing wilayah. Ketiga kriteria direklasifikasi secara Boolean menjadi 1 atau 0 dan dijumlahkan sehingga tiga kriteria terpenuhi menjadi Prioritas 1, dua kriteria Prioritas 2, satu kriteria Prioritas 3, dan tidak ada kriteria terpenuhi menjadi Prioritas 4. Hasil penelitian menunjukkan perbedaan yang jelas pada komposisi vegetasi, konfigurasi lanskap, kondisi termal, dan jasa lanskap. Kabupaten Bogor memiliki PLAND vegetasi pohon tertinggi sebesar 40,21%, AI 86,26%, dan LPI 19,20%, sedangkan Kota Bekasi memiliki PLAND vegetasi pohon 2,13%, AI 48,43%, dan LPI 0,09% serta didominasi lahan terbangun. LST rata-rata meningkat dari Kabupaten Bogor 33,04 °C, Kabupaten Bekasi 36,01 °C, Kota Bogor 39,19 °C, hingga Kota Bekasi 42,30 °C. Proporsi kelas UTFVI buruk hingga paling buruk masing-masing sebesar 15,7%, 27,9%, 67,0%, dan 94,8%. Pada analisis gabungan grid 1 km, PLAND, AI, dan LPI vegetasi pohon berkorelasi negatif dengan LST sebesar -0,781, -0,731, dan -0,775. Estimasi i-Tree Canopy menunjukkan Kabupaten Bogor memiliki tutupan pohon/semak tertinggi sebesar 54,02% dan intensitas simpanan karbon tertinggi 4.151,3 t C/km², sedangkan Kabupaten Bekasi memiliki intensitas terendah 992,8 t C/km² meskipun vegetasi total hasil Landsat mencapai 66,40% karena didominasi vegetasi nonpohon. Zonasi menghasilkan 14,6% sel sebagai Prioritas 1 dan 15,2% sebagai Prioritas 2, sehingga 29,8% unit grid memenuhi sedikitnya dua kriteria. Proporsi gabungan Prioritas 1 dan 2 tertinggi terdapat di Kota Bekasi sebesar 88,1%, diikuti Kota Bogor 62,7%, Kabupaten Bekasi 45,4%, dan Kabupaten Bogor 17,9%. Penelitian menunjukkan bahwa kapasitas RTH dalam mendukung mitigasi UHI tidak cukup dinilai dari luas vegetasi, tetapi perlu mempertimbangkan keberadaan tajuk pohon dan konfigurasi spasialnya. Kabupaten Bogor memperlihatkan kondisi termal paling baik bersamaan dengan tingginya proporsi dan agregasi vegetasi pohon, sedangkan Kota Bekasi menunjukkan tekanan termal paling tinggi dengan tutupan pohon yang sangat rendah. Kabupaten Bekasi menegaskan bahwa luas vegetasi total yang tinggi tidak selalu diikuti kapasitas jasa lanskap yang tinggi apabila vegetasi didominasi vegetasi nonpohon. Arahan mitigasi karena itu perlu disesuaikan dengan karakter wilayah melalui perlindungan hamparan pohon dan pengendalian konversi di Kabupaten Bogor, penguatan jaringan koridor hijau di Kota Bogor, peningkatan tajuk terutama pada kawasan industri serta perlindungan fungsi lahan pertanian di Kabupaten Bekasi, dan penguatan jaringan pohon jalan, ruang publik, koridor riparian, serta ruang hijau kecil di Kota Bekasi. Zonasi yang dihasilkan digunakan sebagai dasar awal dalam menentukan lokasi prioritas pengembangan RTH, sehingga penerapannya tetap memerlukan verifikasi kondisi tapak, kesesuaian dengan RTRW/RDTR, status penguasaan lahan, dan ketentuan sektoral yang berlaku. Hasil penelitian dapat menjadi dasar ilmiah bagi pemerintah daerah dan perencana lanskap dalam merumuskan kebijakan mitigasi UHI, pengendalian pemanfaatan ruang, dan pengembangan RTH yang lebih sesuai dengan tingkat urbanisasi serta karakter lanskap masing-masing wilayah.

Urbanization and land-use conversion in the Jakarta metropolitan region have increased built-up surfaces, reduced vegetation, and intensified urban thermal pressure. Bogor and Bekasi are part of the same metropolitan system but differ in urbanization level, built-up intensity, land use, and vegetation structure, thereby providing a relevant gradient for examining the Urban Heat Island (UHI) phenomenon. Previous studies in these areas have generally explained relationships among land-cover change, vegetation indices, and land surface temperature, but few have integrated tree cover, spatial vegetation configuration, thermal conditions, and landscape services within a single comparative framework. This gap is important because a high proportion of vegetation does not necessarily provide the same thermal mitigation capacity when vegetation is dominated by low-stature vegetation or distributed as small and fragmented patches. This study therefore aimed to: (1) identify the spatial patterns and landscape configuration of tree vegetation; (2) identify the spatial patterns of Surface Urban Heat Island (SUHI); (3) analyze landscape services of tree-based urban green spaces and their descriptive relationships with landscape configuration and land surface temperature; and (4) formulate directions for the development and spatial arrangement of urban green spaces for UHI mitigation across the four study areas in Bogor and Bekasi. Landsat 8 and Landsat 9 imagery from 2025 was used to derive land-cover classification, the Normalized Difference Vegetation Index (NDVI), and Land Surface Temperature (LST). Land cover was classified using a Support Vector Machine (SVM), while tree vegetation configuration was analyzed using percentage of landscape (PLAND), aggregation index (AI), largest patch index (LPI), patch density (PD), and edge density (ED). Thermal conditions were evaluated using LST and the Urban Thermal Field Variance Index (UTFVI) with a pooled reference temperature of 307.60 K. Relationships between tree vegetation configuration metrics and LST were analyzed using Spearman rank correlation at a 1-km grid scale, while canopy cover, carbon storage, carbon sequestration, and pollutant removal were estimated using i-Tree Canopy for comparative assessment among regions. Priority zoning for urban green space development was produced through an overlay of three criteria on a 1 km × 1 km grid. The thermal criterion was defined as LST >37.33 °C based on the 75th percentile of 4,565 cells with valid LST values; the vegetation criterion was defined as tree-vegetation PLAND <5% as an empirical threshold for identifying the most evident tree-cover deficiency; and the social criterion was defined as population density above the median subdistrict density within each region. The three criteria were reclassified using a Boolean approach into values of 1 or 0 and then summed, with cells meeting all three criteria classified as Priority 1, two criteria as Priority 2, one criterion as Priority 3, and no criteria as Priority 4. The results revealed clear differences in vegetation composition, landscape configuration, thermal conditions, and landscape services among the four study areas. Bogor Regency had the highest tree-vegetation PLAND at 40.21%, with an AI of 86.26% and an LPI of 19.20%, whereas Bekasi City had a tree-vegetation PLAND of only 2.13%, an AI of 48.43%, and an LPI of 0.09%, and was dominated by built-up land. Mean LST increased from 33.04 °C in Bogor Regency to 36.01 °C in Bekasi Regency, 39.19 °C in Bogor City, and 42.30 °C in Bekasi City. The proportions of poor to poorest UTFVI classes were 15.7%, 27.9%, 67.0%, and 94.8%, respectively. In the pooled 1-km grid analysis, tree-vegetation PLAND, AI, and LPI were negatively correlated with LST, with coefficients of -0.781, -0.731, and -0.775, respectively. i-Tree Canopy estimates showed that Bogor Regency had the highest tree/shrub cover at 54.02% and the highest carbon-storage intensity at 4,151.3 t C/km², while Bekasi Regency had the lowest intensity at 992.8 t C/km² despite total vegetation cover of 66.40% from Landsat classification, because most of this vegetation was non-tree vegetation. The zoning analysis classified 14.6% of cells as Priority 1 and 15.2% as Priority 2, meaning that 29.8% of all grid cells met at least two priority criteria. The combined proportion of Priority 1 and Priority 2 was highest in Bekasi City at 88.1%, followed by Bogor City at 62.7%, Bekasi Regency at 45.4%, and Bogor Regency at 17.9%. The study demonstrates that the capacity of urban green spaces to support UHI mitigation cannot be assessed solely from total vegetation area, but should also consider the presence of tree canopy and its spatial configuration. Bogor Regency exhibited the most favorable thermal conditions together with the highest proportion and aggregation of tree vegetation, whereas Bekasi City showed the greatest thermal pressure and very limited tree cover. Bekasi Regency further demonstrates that a high total vegetation proportion does not necessarily correspond to high landscape-service capacity when vegetation is dominated by non-tree cover. Mitigation directions should therefore be tailored to regional characteristics through protection of extensive tree patches and control of land conversion in Bogor Regency; strengthening green-corridor networks in Bogor City; increasing tree canopy, particularly in industrial areas and along tree corridors, while maintaining protected agricultural land functions in Bekasi Regency; and strengthening street-tree networks, public green spaces, riparian corridors, and small green spaces in Bekasi City. The zoning results provide an initial basis for determining priority locations for urban green space development, while implementation still requires site verification, consistency with spatial plans (RTRW/RDTR), land-tenure information, and applicable sectoral regulations. The findings can provide a scientific basis for local governments and landscape planners in formulating UHI mitigation policies, controlling land use, and developing urban green spaces that are better aligned with the urbanization level and landscape characteristics of each region.